3 Big Email Marketing Mistakes That Are Hurting Your Campaigns

Unfortunately, we’ve all been there. Each and every one of us have made cringeworthy mistakes in our lives—some of which haunt us to this very day. I still remember the day I asked my crush to prom without checking beforehand if she had a boyfriend. As you can imagine, it didn’t go well (but at least I got to keep the flowers).

But whether you split your pants or forget your pants altogether, the mistakes that we make in our personal lives often aren’t as public as email marketing mistakes. We’re talking about the difference between a few people knowing versus a few hundred thousand people knowing—a whole new level of embarrassment that your childhood self couldn’t even fathom.

To keep your email marketing campaigns in check and save you from massive levels of embarrassment, I’ve put together the three biggest mistakes that email marketers make and how you can fix them:

1. Bad A/B Testing Decisions

Honestly, who doesn’t love to run a good A/B test? You feel like a mad scientist the moment you push send. Heck, I’ve even lost sleep over A/B tests before from overwhelming excitement. However, seeing less than optimal results from poor testing decisions can cause a lack of sleep, but this time, caused by stress.

These are a few common testing errors that can hurt your results:

Sample size too small: Your data set needs to be large enough in order to really prove that you can roll out a change to all of your email campaigns without hurting their performance. As a good rule of thumb, I like to make sure I have at least 1,000 observations for every test I run to reach statistical significance. This means that I’ll wait until I have at least 1,000 opened emails for each email (control and test) before declaring a winner.

But what if your emails never reach 1,000 opens? To make sure your test can reach statistical significance, you need to back into the numbers when selecting your sample size. Look at the average opens rates for your selected audience and choose the sample size based on being able to predict at least 1,000 opens per email. Also, run two to three tests to confirm that you do, in fact, have a true winner. In my experience, I’ve found many times that the winner the first time can lose the second time.

Too many variables: For any A/B test, one of the most critical things you need to do is normalize your testing environment to minimize extraneous variables as much as possible. It’s easy to want to test more than one variable because you think the more you test at once, the bigger the impact you can make and the faster you can optimize your emails. But the challenge is that you don’t actually know the incremental increases or decreases in each variable. Even a send time difference of 30 minutes between your control and test email can drastically change your results.

Let’s say that you’re testing three variables at once in an email: the copy, CTA, and banner. You run the test against the control with a large enough sample size to see statistical significance and then run it three more times to prove it out. If you see that the test beats the control by an open rate of 12% and a click-to-open rate of 36%, how do you confidently declare what copy, CTA, and banner will work best across all your other campaigns? You can’t. Not to mention, when it comes to your banner image, if the recipient has a preview pane and could see the email before images were downloaded (and you had an HTML button), your results would be significantly skewed.

2. Poor Email List Hygiene

Not maintaining your email lists is kind of like giving up on brushing your teeth. It’s just gross. Just like teeth, email list hygiene comes down to cleaning and maintaining everything that goes into your database.

Most emails probably come into your database through an opt-in process. In a single opt-in, a new name fills out a web form and is automatically added to your subscription list. For a double opt-in, a new name fills out a web form and then a confirmation email is triggered with a link to confirm the email address.

Many marketers choose the single opt-in method because you’re able to capture more names since subscribers don’t have to jump through hoops. However, this comes at the cost of seeing fake emails or emails with syntax errors, higher soft and hard bounce rates, a lower sender reputation, less email engagement, and ultimately less qualified names. But with the proper hygiene practices in place, you can clean up your database over time to maintain a healthy email list.

Here’s what you need to have in place with a single opt-in method:

Soft bounce management campaigns: Since you haven’t confirmed that every new email address is 100% valid, you’ll have higher soft bounce and hard bounce rates. Hard bounced email addresses are usually taken care of by your marketing automation system or email service provider, so you won’t need to worry about managing those. But for soft bounces, you can create automated campaigns that clean up all email addresses that repeatedly soft bounced both in the past and in real-time. This will help clean your lists, increase your open rates, and keep your sender reputation high.

Remove role accounts: A role account is an email address like info@, support@, or abuse@ that is not associated with a particular person. There are three reasons why these should be removed:

It’s impossible to prove that everyone who will receive emails at these addresses has given their consent.

These addresses are commonly found on the “Contact Us” page of websites, which makes them more susceptible to being harvested.

Blacklist providers use role accounts as honeypot spam traps in an attempt to catch spammers.

Re-engagement campaigns: A marketer typically has a list of subscribers with as many as 25-50% of these people classified as “inactive.” You can run reactivation campaigns to target subscribers who haven’t engaged with your emails in six months or more to determine who still wants to hear from you, who doesn’t want to hear from you (an unsubscribe is better than being marked as spam), and clean out your email lists.

3. Unclear Subject Lines

Clear usually beats clever because clear subject lines are more consistent with the body of your email, which accounts for higher raw clicks. No tricks, no clickbait, and no questions about what the email actually contains. In fact, clear subject lines receive 541% more clicks than clever ones, according to a study by AWeber Communications.

A few examples of clever subject lines that I’ve seen are “You’re not alone,” “It’s finally here,” and “Still doing it the old way?” While emails with these subject lines might be opened by your subscribers out of curiosity, more likely than not the the links within won’t be clicked on. While clear subject lines might not seem as sexy or luring, they work exceedingly well when your goal is to achieve higher click-through rates.

Have you made a cringeworthy email marketing mistake? Share it in the comments below and explain how you recovered from it!

We will handle your contact details in line with our
Privacy Policy. If you prefer not to receive marketing emails
from Marketo, you can opt-out of all marketing communications or customize your preferences
here.